Tourist Flows and Multi-Destination Trips: A Network Analysis

Abstract

ABSTRACT Conventional approaches to modeling multi-destination trips are either based on trade-offs between one single destination and multiple destinations or on a sequence of destinations in a linear manner. These approaches are inadequate to capture the manifestation of multi-destination trips as a network at the aggregate level. Hence, built upon network analytical frameworks, this study adopted a directed network to model multi-destination trips. Using a visitor profile survey of Hong Kong, we found that the networks of multi-destination trips for both leisure and business travelers have several interesting properties, such as high densities, high clustering coefficients, and short diameters. High-degree nodes represent either destinations or origins in the leisure network, but they have a dual role as both destinations and origins in the business network. Network sparsity has a significant impact on the topology of the leisure network, but the impact is negligible on the business network.